Physical parameters in relation to physiological changes of avocado during ripening (20ºc) and cold storage (6ºc) in different conditions.

The application of the response of fruits to low energy for mechanical impacts is described, for evaluation of post-harvest ripening of avocadoes of the variety "Hass". An impactor of 50g of weight, provided with an accelerometer, and free-falling from a height of 4 cm, is used; it is interfaced to a computer and uses a special software for retrieving and analyzing the deceleration data. Impact response parameters of individual fruits were compared to firmness of the pulp, measured by the most used method of double-plate puncture, as well as to other physical and physiological parameters: color, skin puncture ethylene production rate and others. Two groups of fruits were carefully selected, stored at 6º C (60 days) and ripened at 20ºC (11 days), and tested during the storage period. It is shown that, as in other types of fruits, impact response can be a good predictor of firmness in avocadoes, obtaining the same accuracy as with destructive firmness measurements. Mathematical and multiple regression models are calculated and compared to measured data, with which a prediction of storage period can be made for these fruits.

Fruit quality sensing:Post-harvest ripeness

Firmness sensing of selected varieties of apples, pears and avocado fruits has been developed using a nondestructive impact technique. In addition to firmness measurements, postharvest ripeness of apples and pears was monitored by spectrophotometric reflectance measurements, and that of avocadoes by Hunter colour measurements. The data obtained from firmness sensing were analyzed by three analytical procedures: principal component, correlation and regression, and stepwise discriminant analysis. A new software was developed to control the impact test, analyse the data, and sort the fruit into specified classes, based on the criteria obtained from a training procedure. Similar procedures were used to analyse the reflectance and colour data. Both sensing systems were able to classify fruits w i th good accuracy.