Quantitative Tools and Procedures for Shelf Life Determination in Minimally Processed Fruits and Vegetables

  • A. Possas
  • F. J. Benítez
  • D. Savran
  • N. J. Brotóns
  • P. J. Rodríguez
  • G. D. Posada-Izquierdo
Part of the Food Microbiology and Food Safety book series (FMFS)


In minimally processed fruits and vegetables (MPFV) the exposure of internal tissues, the lack of skin or cuticle and the accelerated metabolism after processing lead to deterioration of sensory attributes mainly due to biochemical processes, physiological ageing and microbial spoilage. Therefore, processing operations such as peeling, slicing or shredding make MPFV more perishable than intact fresh produce. Shelf life of these products is not homogenous and can greatly vary mainly due to differences in manufacturing processes to which they are subjected. Reliable techniques that allow determining shelf life in an effective and precise way are necessary, as small changes in shelf life determinations could represent big economic losses. The shelf life of MPFV is usually determined by means of methods that evaluate changes in organoleptic characteristics during the distribution chain. Hence, it is essential to understand the processes influencing changes in MPFV quality as well as treatments and management techniques that are applied to evaluate and monitor their quality. Innovative techniques that allow modelling the influence of different environmental conditions and processing operations on MPFV quality are being proposed as more objective techniques to determine shelf life. Within these innovative procedures, shelf life estimation by means of the use of predictive microbiology models is one of the most useful ones. The purpose of this chapter is to provide an overview on processes influencing quality changes of minimally processed fruits and vegetables as well as the available procedures and quantitative tools that are applied in shelf life determination.


Fresh-cut products Minimal processing Shelf life estimation methods Quality deterioration Laboratory methods Predictive microbiology models 


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • A. Possas
    • 1
  • F. J. Benítez
    • 2
  • D. Savran
    • 3
  • N. J. Brotóns
    • 2
  • P. J. Rodríguez
    • 2
  • G. D. Posada-Izquierdo
    • 1
  1. 1.Department of Food Science and Technology, International Campus of Excellence in the AgriFood SectorUniversity of CórdobaCórdobaSpain
  2. 2.Biotechveg SA LaboratoriesAlicanteSpain
  3. 3.Department of Food EngineeringUniversity of AnkaraAnkaraTurkey

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