Optimization of controlled atmosphere storage conditions to export 'palmer' mango

The main objective of this study was to preserve the quality of ‘Palmer’ mangoes exported for the supply chain in Europe, and the specific objectives were: I. establish the best maturity stage for sea freight transportation and under controlled atmosphere (CA) conditions, determined using non-destructive of techniques near infrared spectroscopy; II. develop calibration and prediction models for dry matter (DM) and soluble solids content (SSC), III. compare if the proposed approach differs from the traditional mango handling to sea freight to Europe. In the study about the determination of the ‘Palmer’ mangoes maturity stages using near portable infrared spectrometer (VIS-NIR), the best calibration model for SSC was obtained using NIR spectra pre-processed with standard normal variation (SNV), first derivative of Savitizk-Golay, and 699-999 nm window. For SSC, it was observed a RMSECV of 1.39 %, with a R2CV of 0.87, and a RPD of 2.77. Better results could be seen for the DM calibration model built with raw spectra using the 699-981 nm window (RMSECV of 8.81 g.kg-1, R2CV of 0.84 and RPD of 2.51), and poor calibration models were obtained for firmness. In the study about refrigerated storage of ‘Palmer’ mangos sorted based on their DM content using near portable infrared spectrometer (VIS-NIR), it could be seen that the PLS model developed during 2015/2016 mango season was not appropriate to predict the DM content of fruit from 2016/2017 season (R² not adjusted). Therefore, the VIS-NIR spectra from 2016/2017 season were incorporated into the dataset and a new model was developed (RMSEcv of 10.5 g.kg-1, R²P of 0.75). With the new model, ‘Palmer’ mangoes were sorted in two maturity stages (150 g.kg-1 and 110 g.kg-1), which resulted in quality differences, mainly in relation to DM and SSC. In the study about the postharvest responses of mangos non-destructively sorted based on DM content during and after the storage under controlled atmosphere (CA), it was observed that the partial least squares regression (PLSR) model developed with fruit from 2015/2016 and 2016/2017 from Candido Rodrigues - SP, was able to properly predict the DM content of mangoes produced in Petrolina - PE, but with a high root mean square error of prediction (RMSEP = 20.2 g kg-1) and low R2P (0.19). Therefore the VIS-NIR spectra from mangoes produced in Petrolina – PE were incorporated into the dataset and a new model was developed (RMSEv of 13.8 g kg-1 and R²V of 0.63). With the new PLSR model, it was possible to sort mangoes produced in Petrolina – PE with 150 g.kg-1 DM, confirming the robustness of the model. It was not observed significant quality differences between fruit sorted based on DM (150 g.kg-1) in relation to visual appearance sorted fruit (traditional handling) during CA storage (5 kPa O2 and 5 kPa CO2) for up to 30 days at 14.2±2.3 °C and 92.6±2.8 % RH. However, the mangoes sorted with 150 g.kg-1 DM showed lower standard deviation, indicating a more homogeneous fruit batch. All in all, it was possible to preserve the quality of ‘Palmer’ mango to be exported to Europe, mainly by sorting the fruit in the appropriate maturity stage (150 g.kg-1 DM) with a more homogeneous fruit batch. (AU)