Application of uncertain data handling on the assessment of tomato quality

Luis F. Rodriguez, Catalin Moraru, Tung Ching Lee, Alfred B.O. Soboyejo, Christopher M. Gregson, Darwin Poritz

Research output: Contribution to journalConference article

Abstract

The handling of uncertain data is demonstrated on an empirical grading function used for the assessment of tomato quality. The grading function studied here is designed to measure the departure of the properties of a tomato or a population of tomatoes from an assumed optimal tomato. Uncertain data are considered using the Taylor Series expansion of the grading function, a function of random variables, which provides the ability to determine the variability of the outcome of the function. Once this variability is quantified, confidence intervals are determined and considered. The degree of confidence in a result has a wide array of ramifications, ranging from providing valuable decision support to assisting in guidance of research activity. Results of this analysis are useful for the Advanced Life Support (ALS) community, as the application of the Taylor Series expansion is not limited to grading functions alone, but can be applied to any model where information describing the variability of the model inputs is available.

Original languageEnglish (US)
JournalSAE Technical Papers
DOIs
StatePublished - Jan 1 2003
Externally publishedYes
Event33rd International Conference on Environmental Systems, ICES 2003 - Vancouver, BC, Canada
Duration: Jul 7 2003Jul 10 2003

ASJC Scopus subject areas

  • Automotive Engineering
  • Safety, Risk, Reliability and Quality
  • Pollution
  • Industrial and Manufacturing Engineering

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