Metabolic Profiling and Post-harvest Behavior of "Dottato" Fig (Ficus carica L.) Fruit Covered With an Edible Coating From O. ficus-indica.

Alessio Allegra,Francesco Mercati,Alessandra Gallotta,Paolo Inglese,Federico Martinelli,Francesco Carimi

doi:10.3389/fpls.2018.01321

Abstract

Fig fruits are usually highly sensitive to some physiopathological disorders during post-harvest life, such as softening and skin cracking. Indeed, the use of edible coating (EC) has been evaluated in several fruit crops to reduce fruit post-harvest transpiration and to maintain fruit visual quality. The aim of this study was to determine the post-harvest metabolic response of breba figs treated with mucilage extract from O puntia ficus-indica cladodes, using an untargeted metabolomic approach. Coated and non-coated (control) fruit were sealed in plastic bags, and stored at 4°C for 7 days. The effect of the ECs on their quality fruit during cold storage and qualitative attributes were evaluated by analyzing the fruit primary metabolism and other qualitative parameters such as total soluble solids (TSS) content, titratable acidity (TA), fresh weight loss and firmness. Results underlined that EC was effective in maintaining fruit fresh weight, and fruit firmness. Stepwise discriminant analysis was able to discriminate fruit conditions. Alanine, xylulose, aspartic acid, glutamic, acid and 2,5-dihydroxypyrazine showed a significant role on discriminating edible coated fruit from untreated ones. Principal component analysis (PCA) was able to highlight clear differences in the overall metabolism changes between untreated and treated fruit. The application of EC significantly mitigated the decrease of most of the aminoacid content during cold storage. EC treatment caused the changes of several organic acids in comparison to untreated control, increasing the amount of carbohydrates and other key metabolites, such as beta-sitosterol, glycerol, and uracil. These results clearly showed the drastic effects of EC on fig metabolism during post-harvest and shed light on the beneficial mechanisms of this treatment.

Highlights

Fig (Ficus carica L.) is native to western Asia and has been cultivated and consumed in the Mediterranean Basin since the earliest stages of the agricultural civilization (Accademia dei Georgofili, 2003)
Fruits were immediately dipped in chlorinated water (100 ppm of free chlorine) for 6 min and placed in bi-oriented polystyrene (PS) macroperforated bags (Carton Pack s.r.l., Rutigliano, Italy) used in another work on the Breba fig (Allegra and Colelli, 2017) Eighteen fruits were treated with a mucilage coating solution (MC), extracted from Opuntia ficus-indica (OFI) (Sepulveda et al, 2007; Allegra et al, 2016, 2017), for 60 s; the exceeding coating was drained and the coated figs were dried in a forced-air dryer (20◦C) for 30 min
The non-targeted metabolomic analysis displayed a total of 176 peaks, 112 of which were identified though a comparison with the Agilent Fiehn GCgas chromatographer (GC)/mass spectrometer (MS) Metabolomics RTL Library and mass spectra interpretation (Supplementary Table S1)

Summary

Introduction

Fig (Ficus carica L.) is native to western Asia and has been cultivated and consumed in the Mediterranean Basin since the earliest stages of the agricultural civilization (Accademia dei Georgofili, 2003). “Dottato” fig is an ancient bifera type cultivated variety originated in Italy and most important in Southern Italy, in the areas of Cilento, Calabria, and Sicily It can produce two crops; the first crop (brebas) is parthenocarpic and fruit are named as brebas, while the second crop produces seeded figs only after pollination. In Italy, breba figs are harvested from the end of June to the beginning of July, while “Forniti” (name for the second harvest) are harvested from early August to late September (Allegra et al, 2017). Both brebas and common figs are climacteric fruits and are slightly sensitive to high temperature on stimulating softening and decay severity. Metabolic approach is usually seen as complement to transcriptomics and proteomics because metabolic reactions are usually modulated by transcript and protein abundance and by

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