Firmness prediction of 'Rocha' pear based on non-destructive methods and shelf-life using PLS-regression modeling

Knowledge of fruit firmness in the distribution chain is essential for stakeholders, including producers, agri-food industries, and consumers. In recent years, there has been a general interest in predicting ripening-related firmness with non-destructive techniques. The objective of this study was to create a model, based on non-destructive methods that assess directly critical physiological parameters and quality attributes related to ripening, along with shelf-life time, to predict firmness of 'Rocha' pear (Pyrus communis L.), a protected designation of origin (PDO) commodity. Hereto, pear firmness profile was assessed for ten days at room temperature, after removal from different storage periods at cold conditions. Ripening was evaluated based on color alterations, ethylene production, and respiration rate. Pear firmness decreased drastically over time, concomitant with the yellowing of the fruit skin and increased ethylene production and respiration rate. These characteristics and shelf-life time were correlated with firmness by applying the Partial Least Squares (PLS) procedure to develop a mathematical model for predicting pear firmness during ripening. The model explained 89 % of the firmness variance during ripening and, after validation, showed high accuracy (R2 = 0.87). To the best of our knowledge, this is the first time that these physiological parameters, directly related to ripening-firmness, have been used to predict pear firmness using non-destructive measurements of the samples.