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Fresh-cut processing is a good strategy to enhance the commercialization of peaches and nectarines, which easily deteriorate during low-temperature storage mostly due to the occurrence of chilling injury. Although several studies have been performed to improve the shelf-life of fresh-cut stone fruit, the achievement of high-quality fresh-cut peaches and nectarines still constitutes a challenge. The present study aimed to gain insights into the evolution of the postharvest quality of fresh-cut nectarines ( Prunus persica L. Batsch) Big Bang, cold-stored at two different storage temperatures (4 and 8 °C) for up to 10 days. Several aspects influencing the quality traits (sensory and postharvest quality parameters; the profile of phenolic and volatile organic compounds (VOCs)) were explored to predict the marketable life of the fresh-cut nectarines. The respiration rate was higher in samples stored at 4 °C, while the browning process was more evident in fruit stored at 8 °C. Partial Least Squares Regression performed on VOCs showed that samples stored at 4 °C and 8 °C presented a different time evolution during the experiment and the trajectories depended on the interaction between time and temperature. Moreover, Multiple Linear Regression analysis discovered that the 17 VOCs affected by the storage conditions seemed to suggest that no chilling injury was detected for nectarines Big Bang. In conclusion, this approach could also be used with other nectarine cultivars and/or different stone fruits.

Electronic nose (e-nose), attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy and image analysis (IA) were used to discriminate the ripening stage (half-red or red) of strawberries (cv Sabrosa, commercially named Candonga), harvested at three different times (H1, H2 and H3). Principal component analysis (PCA) performed on the e-nose, ATR-FTIR and IA data allowed us to clearly discriminate samples based on the ripening stage, as in the score space they clustered in distinct regions of the plot. Moreover, a correlation analysis between the e-nose sensor and 57 volatile organic compounds (VOCs), which were overall detected in all the investigated fruit samples by headspace solid-phase microextraction coupled to gas chromatography-mass spectrometry (HS-SPME/GC-MS), allowed us to distinguish half-red and red strawberries, as the e-nose sensors gave distinct responses to samples with different flavours. Three suitable broad bands were individuated by PCA in the ATR-FTIR spectra to discriminate half-red and red samples: the band centred at 3295 cm -1 is generated by compounds that decline, whereas those at 1717 cm -1 and at 1026 cm -1 stem from compounds that accumulate during ripening. Among the chemical parameters (titratable acidity, total phenols, antioxidant activity and total soluble solid) assayed in this study, only titratable acidity was somehow correlated to ATR-FTIR and IA patterns. Thus, ATR-FTIR spectroscopy and IA might be exploited to rapidly assess titratable acidity, which is an objective indicator of the ripening stage.

The volatile profiles of eight saffron samples (seven cultivated and one spontaneous) grown in different geographical districts within the Campania region (southern Italy) were compared. Using headspace solid-phase microextraction coupled to gas chromatography-mass spectrometry (HS-SPME/GC-MS), overall, 80 volatiles were identified in the eight landraces. Among them, safranal and its isomers and other related compounds such as isophorones, which are not only key odorants but also pharmacologically active metabolites, have been detected in all the investigated samples. Principal Component Analysis performed on the volatiles' compounds revealed that the spontaneous sample turned out to be an outlier. In particular, the volatile organic compounds (VOCs) profile of the spontaneous saffron presented four lilac aldehydes and four lilac alcohol isomers, which, to the authors' knowledge, have never been identified in the volatile signature of this spice. The multivariate statistical analysis allowed the discrimination of the seven cultivate saffron ecotypes in four well-separated clusters according to variety. Moreover, 20 VOCs, able to differentiate the clusters in terms of single volatile metabolite, were discovered. Altogether, these results could contribute to identifying possible volatile signature metabolites (biomarkers) or patterns that discriminate saffron samples grown in Campania region on a molecular basis, encouraging future biodiversity programs to preserve saffron landraces revealing valuable genetic resources.

Understanding the composition of human milk (HM) can provide important insights into the links between infant nutrition, health, and development. In the present work, we have longitudinally investigated the metabolome of milk from 36 women delivering preterm at different gestational ages (GA): extremely (<28 weeks GA), very (29-31 weeks GA) or moderate (32-34 weeks GA) premature. Milk samples were collected at three lactation stages: colostrum (3-6 days post-partum), transitional milk (7-15 days post-partum) and mature milk (16-26 days post-partum). Multivariate and univariate statistical data analyses were performed on the 1 H NMR metabolic profiles of specimens in relation to the degree of prematurity and lactation stage. We observed a high impact of both the mother's phenotype and lactation time on HM metabolome composition. Furthermore, statistically significant differences, although weak, were observed in terms of GA when comparing extremely and moderately preterm milk. Overall, our study provides new insights into preterm HM metabolome composition that may help to optimize feeding of preterm newborns, and thus improve the postnatal growth and later health outcomes of these fragile patients.