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The effect of storage conditions on flavor-related volatile composition of wild rocket () was investigated on Modified Atmosphere packed (MAP) leaves stored under isothermal and non-isothermal conditions. In a first experiment the effect of MAP was compared to the storage in air at 5 °C; a second experiment aimed to study the effect of non isothermal conditions, with two temperature abuses (at 13 °C for 24 h) during a 5 °C. Twenty-four volatiles were detected, including C6, C5, isothiocyanate, lipid-derived and sulfur compounds. In the first experiment, MAP-stored rocket showed a slower loss of typical flavour volatiles (thiocyanates and isothiocyanates) and a slower production of off-flavors until 6 days of storage, compared to leaves stored in air. After this time, dimethyl sulfide and acetaldehyde dramatically increased in MAP-stored rocket samples. In the second experiment, samples stored under non-isothermal conditions showed lower O and higher CO concentrations than samples stored under isothermal conditions. Rocket leaves stored under non-isothermal conditions showed an increased production of volatiles responsible of off-flavors (acetaldehyde and dimethyl sulfide) following temperature abuse comparing to storage in isothermal condition. Thus, dimethyl sulfide and acetaldehyde could be effective markers for tracking the effect of temperature fluctuations on rocket during storage.

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The potential of hyperspectral imaging for the prediction of the internal composition of goji berries was investigated. The prediction performances of models obtained in the Visible-Near Infrared (VIS-NIR) (400–1000 nm) and in the Near Infrared (NIR) (900–1700 nm) regions were compared. Analyzed constituents included Vitamin C, total antioxidant, phenols, anthocyanin, soluble solids content (SSC), and total acidity (TA). For vitamin C and AA, partial least square regression (PLSR) combined with different data pretreatments and wavelength selection resulted in a satisfactory prediction in the NIR region obtaining the R2pred value of 0.91. As for phenols, SSC, and TA, a better performance was obtained in the VIS-NIR region yielding the R2pred values of 0.62, 0.94, and 0.84, respectively. However, the prediction of total antioxidant and anthocyanin content did not give satisfactory results. Conclusively, hyperspectral imaging can be a useful tool for the prediction of the main constituents of the goji berry (Lycium barbarum L.).