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Neuronal network analyses reveal novel associations between volatile organic compounds and sensory properties of tomato fruits

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Abstract

Introduction

The process of tomato (Solanum lycopersicum) breeding has affected negatively the fruit organoleptic properties and this is evident when comparing modern cultivars with heirloom varieties. Flavor of tomato fruit is determined by a complex combination of volatile and nonvolatile metabolites that is not yet understood.

Objectives

The aim of this work was to provide an alternative approach to exploring the relationship between tomato odour/taste and volatile organic compounds (VOCs).

Methods

VOC composition and organoleptic properties of seven Andean tomato landraces along with an edible wild species (Solanum pimpinellifolium) and four commercial varieties were characterized. Six hedonic traits were analyzed by a semitrained sensory panel to describe the organoleptic properties. Ninety-four VOCs were analyzed by headspace solid phase microextraction/gas chromatography–mass spectrometry (HS/SPME/GC–MS). The relationship between sensory data and VOCs was explored using an Artificial Neural Networks model (Kohonen Self Organizing Maps, omeSOM).

Results and Conclusion

The results showed a strong preference by panelists for tomatoes of landraces than for commercial varieties and wild species. The predictive analysis by omeSOM showed 15 VOCs significantly associated to the typical and atypical tomato odour and taste. Moreover, omeSOM was used to predict the relationship of VOC ratios with sensory data. A total of 108 VOC ratios out of 8837 VOC ratios were predicted to be contributing to the typical and atypical tomato odour and taste. The metabolic origin of these flavor-associated VOCs and the metabolic point or target for breeding strategies were discussed.

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Acknowledgements

The authors would like to acknowledge the sensory panel (Facultad de Agronomia, Universidad Nacional de Cuyo) and Georgina Stegmayer and Diego Milone for technical assistance in omeSOM analysis.

Funding

This study was funded in part by ANPCyT (PICT 2007-1942), CONICET, SECYT-UNC, INTA and the European Union Horizon 2020 Research and Innovation Programme, Grant Agreement Number 679796.

Author information

Authors and Affiliations

  1. INFIQC, Departamento de Química Orgánica, Facultad de Ciencias Químicas, Universidad Nacional de Córdoba, Ciudad Universitaria, 5000, Córdoba, Argentina

    Pablo R. Cortina & Ana N. Santiago

  2. IADIZA, CCT-CONICET Mendoza, Parque General San Martín, 5500, Mendoza, Argentina

    María M. Sance & Iris E. Peralta

  3. Facultad de Ciencias Agrarias, Universidad Nacional deCuyo y CCT CONICET Mendoza, Chacras de Coria, Lujan de Cuyo, 5505, Mendoza, Argentina

    Iris E. Peralta

  4. Instituto de Biotecnología, Instituto Nacional de Tecnología Agropecuaria (IB-INTA), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), PO Box 25, B1686WAA, Castelar, Argentina

    Fernando Carrari

  5. Departamento de Botânica, Instituto de Biociências, Universidade de São Paulo, Rua do Matão, 277, São Paulo, 05508-090, Brazil

    Fernando Carrari

  6. CIBICI, Departamento de Bioquímica Clínica, Facultad de Ciencias Químicas, Universidad Nacional de Córdoba, Ciudad Universitaria, 5000, Córdoba, Argentina

    Ramón Asis

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  1. Pablo R. Cortina
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  2. Ana N. Santiago
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  3. María M. Sance
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  4. Iris E. Peralta
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  5. Fernando Carrari
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  6. Ramón Asis
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Corresponding author

Correspondence to Ramón Asis.

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Conflict of interest

All authors declare that they have no conflict of interest.

Ethical approval

The sensory study was approved by the committee of the food science department of the National University of Cuyo. This committee established ethical criteria and protocols for sensorial panels to evaluate fresh and processing products based on the legislation provided by the National Administration of Medicine, Food and Medical Technology of Argentina (ANMAT) and National Food Code.

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11306_2018_1355_MOESM1_ESM.tif

Fig. S1. Map 30×30 of VOC ratios and sensory data. Grey and dark grey squares represent neurons with metabolites and sensory variables, respectively. Black square represent neurons with both variables. Sizes square represent the amount of variables inside the neurons. (TIF 1974 KB)

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Cortina, P.R., Santiago, A.N., Sance, M.M. et al. Neuronal network analyses reveal novel associations between volatile organic compounds and sensory properties of tomato fruits. Metabolomics 14, 57 (2018). https://doi.org/10.1007/s11306-018-1355-7

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  • DOI: https://doi.org/10.1007/s11306-018-1355-7

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