Singular approach to penetrometry by preprocessing of digitized force-displacement curves and chemometry: A case study of 12 tomato varieties.

Unlabelled: This study evaluated a singular approach to the analysis of digitized force-displacement curves from penetrometry performed on tomatoes. Penetrometry is commonly used to evaluate the texture properties of fresh fruits and vegetables. Currently, the parameters are computed from force-displacement curves. The parameters are statistically analyzed to highlight differences, for instance, between fruit varieties or differentially stored fruits. In this study, digitized force-displacement curves were considered "mechanical imprints" (MIs). Twelve varieties of tomato were analyzed, and the assumption that a given variety is characterized by a singular MI was tested. The digitized curves were preprocessed through standardization and smoothing. This preprocessing enabled the classification of more than 94% of fruit according to variety compared with 45% of fruit without preprocessing. To compare this approach with a classical approach of texture analysis, 13 parameters were computed from the force-displacement curves and analyzed. This parameters-based approach enabled the classification of approximately 46% of fruit according to variety. The digitized curve enabled the correct classification of 88% more fruit than the level achieved by the parameters-based approach. Thus, penetrometry analysis presents new opportunities, particularly for breeding programs aimed at improving the texture characteristics of fruits and vegetables. Additionally, this approach could be adapted to other mechanical tests for the characterization of the textural properties of food products.

Practical Applications: The force-displacement curve of penetrometry can be considered a "mechanical imprint" to improve fruit classification according to preharvest and postharvest characteristics (i.e., maturity, variety, etc.). This mechanical imprint represents a new and discriminant phenotyping criterion for tomato breeding to improve texture. The use of the digitized curve rather than computed parameters may be more easily implemented in industry.