Mangoes (Mangifera indica L.) are tropical fruits, which are sourced worldwide to supply the consumer market in Europe. Often mangoes are transported over sea in refrigerated containers at 8–10 °C and in some cases under controlled atmosphere conditions. At arrival in European countries, a vast amount of fruit is ripened under specified conditions to deliver 'Ready to Eat' fruit to consumers. The latter is a challenge due to great variability in fruit maturity stage at arrival. There are currently no good methodologies to rapidly and nondestructively monitor and control the ripening process of mangoes. A major indicator of mango ripeness is fruit firmness. In the present study, a portable visible near-infrared (400–1130 nm) (VNIR) spectrometer was used to predict the firmness of individual mango undergoing ripening. Ripening of ‘Kent’ mango was for 10 days monitored at 20 °C and relative humidity (RH) of 85%. Every other day fruit firmness (measured with AWETA acoustic firmness analyzer) and NIR spectrum were determined on 2 opposite sides of the fruit. Interval partial-least square (iPLSR) regression was used for identifying the important wavelengths responsible for predicting firmness in mangoes. Results showed a change in the VNIR spectra with the change in firmness of mangoes. The model based on selected wavelengths performed significantly better compared to PLSR without pre-selecting wavelengths. iPLSR based regression provided a correlation of calibration and prediction as R2c = 0.75 and R2p = 0.75, and root means squared error of calibration and prediction as 6.02 Hz2g2/3 and 5.92 Hz2g2/3 respectively. The iPLSR model outperformed the standard PLSR model by over 12% in R2p and 14% reduction in prediction error. The predictions by the model provided an evolution of the firmness during the complete ripening experiment. Non-destructive access to mango firmness during ripening can assist in optimizing the process to better meet the market demand.
- Fruit quality
- Variable selection