title: Characterization of the red layer and pericarp of processing tomato using magnetic resonance imaging.
abstract: The characteristics of tomato pericarp are closely associated with peelabililty, an important quality attribute of processing tomatoes. Different types of tissue exist in the pericarp of tomato. The outermost region of the pericarp, the red layer, is removed with the skin during peeling. This study investigated the morphological features and tissue properties of red layer and pericarp for 3 processing tomato cultivars using magnetic resonance imaging (MRI). The red layer can be visualized in MR images with T(2) weighting, indicating the red layer has different properties compared to the rest of the pericarp region. Tomatoes were imaged with a set of MRI sequences with signal intensity dependent on different water proton properties. Principal component analysis (PCA) of the statistical features revealed clustering of fruit by cultivar. The spatial distribution of cultivars in the PCA score plot followed their rank of peeling performance. MRI demonstrated potential as a nondestructive method to characterize tomato pericarp and evaluate the peelability of processing tomatoes.
  
  
  CONCLUSIONS
  Peelability of tomatoes affects the quality of value-added whole peel and diced tomato products. The properties of the pericarp of tomato are directly related to the peelability of tomatoes. MRI provided a fast and nondestructive method to characterize the properties of tomato pericarp. The result of this work gives insight into the correlation between tomato pericarp characteristics and peelability.
authors.affiliation: Department of Food Science and Technology, University of California, Davis, Davis, CA 95616, USA.
authors.forename: Lu
authors.initials: L
authors.lastname: Zhang
authors.forename: Diane M
authors.initials: DM
authors.lastname: Barrett
authors.forename: Michael J
authors.initials: MJ
authors.lastname: McCarthy
mesh_terms: D005069:Evaluation Studies as Topic; D005511:Food Handling / Q000379:methods*; D005524:Food Technology; D007091:Image Processing, Computer-Assisted; D018551:Solanum lycopersicum / Q000737:chemistry*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D025341:Principal Component Analysis