Comparison of image analysis methods to evaluate the degree of browning of fresh-cut lettuce

Jeong Seok Cho, Kwang Deog Moon

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Digital image analysis was used to detect changes in browning of fresh-cut lettuce. Fresh-cut lettuce was divided into the 4 treatment groups of dipping in distilled water (control group); ultrasound treatment for 90 s in distilled water (US); blanching for 90 s at 45°C (BC); and blanching after ultrasound treatment (US+BC). The degree of browning was measured using image analysis, colorimetry, spectrophotometry, and visual assessment. Using image analysis, the US+BC treatment group showed the smallest browning area and lowest b* value. Correlation between visual assessment and image analysis for evaluation of the area of browning was the highest (0.9592), followed by the b* value of image analysis (0.9527). The lowest correlation coefficient (0.6962) was observed between visual assessment and the b* value using colorimetry. Image analysis can be used as a method for evaluating browning in fresh-cut lettuce.

Original languageEnglish
Pages (from-to)1043-1048
Number of pages6
JournalFood Science and Biotechnology
Volume23
Issue number4
DOIs
StatePublished - Aug 2014

Keywords

  • browning degree
  • color
  • freshcut lettuce
  • image analysis
  • MATLAB

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