Predictive Statistical Model for the Analysis of Drop Impact Damage on Peach

✍ Scribed by Paolo Menesatti; Claudio Beni; Graziella Paglia; Simona Marcelli; Stefano D'Andrea

• Publisher: Elsevier Science
• Year: 1999
• Tongue: English
• Weight: 235 KB
• Volume: 73
• Category: Article
• ISSN: 0021-8634
• DOI: 10.1006/jaer.1999.0417

✦ Synopsis

The susceptibility of a fruit cultivar to di!erent types of mechanical stresses was investigated in order to set limits for intensity and type of impacts, during handling operations.

The present work reports a statistical forecast model to analyse the damage susceptibility of peaches (cv Fairtime) as a function of di!erent fruit physical and morphological variables (mass, volume, density, equatorial diameter, height), of the impact method used (drop tests performed using impact devices which were specially designed by the authors) and of variables related to the impact event (damage location on fruit). Drop heights were chosen randomly, ranging between 200 and 600 mm.

The experiment was based on a multiple linear regression model (MLR) operating on the independent variables mentioned. The resulting model was shown to be highly signi"cant (correlation coe$cient of 0)82) and included among the variables related to the average damage: drop height, fruit density, pulp thickness at the point of impact and distance of the point of impact from the insertion of the peduncle. These latter two variables both present a negative coe$cient which agrees with the morphological type of damage, con"ned to the interior of the mesocarp of the drupe very near the ligneous endocarp. Calculation using the MLR equations estimated a very low probability of slight damage (values of damage extension between 3 and 10 mm) for peaches falling as much as 400 mm.