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Updated: Jul 6, 2025

Isolation and Biophysical Study of Fruit Cuticles
Published on: March 30, 2012
A comprehensive study from the micro- to the nanometric scale: Evaluation of chilling injury in tomato fruit (Solanum
C I Acosta-Ramírez1, I D Lares-Carrillo2, L E Ayón-Reyna3
1Facultad de Ciencias Químico Biológicas, Universidad Autónoma de Sinaloa, Ciudad Universitaria, Culiacán, Sinaloa 80013, Mexico; Instituto Politécnico Nacional, Escuela Nacional de Ciencias Biológicas, Carpio y Plan de Ayala S/N, Ciudad de México 11340, Mexico.
Abstract:
Tomato fruit is susceptible to chilling injury (CI) during its postharvest handling at low temperature. The symptoms caused by this physiological disorder have been commonly evaluated by visual inspection at a macro-observation scale on fruit surface; however, the structure at deeper scales is also affected by CI. This work aimed to propose a descriptive model of the CI development in tomato tissue under the micro-scale, micro-nano-scale and nano-scale approaches using fractal analysis. For that, quality and fractal parameters were determined. In this sense, light microscopy, Environmental Scanning Electron Microscopy (ESEM) and Atomic Force Microscopy (AFM) were applied to analyse micro-, micro-nano- and nano-scales, respectively. Results showed that the morphology of tomato tissue at the micro-scale level was properly described by the multifractal behaviour. Also, generalised fractal dimension (Dq=0) and texture fractal dimension (FD) of CI-damaged pericarp and cuticle were higher (1.659, 1.601 and 1.746, respectively) in comparison to non-chilled samples (1.606, 1.578 and 1.644, respectively); however, FD was unsuitable to detect morphological changes at the nano-scale. On the other hand, lacunarity represented an appropriate fractal parameter to detect CI symptoms at the nano-scale due to differences observed between damaged and regular ripe tissue (0.044 and 0.025, respectively). The proposed multi-scale approach could improve the understanding of CI as a complex disorder to the development of novel techniques to avoid this postharvest issue at different observation scales.

