Image analysis for assessment of light-induced greening of potato tubers (Solanum tuberosum L.).

Date

5-2013

Degree

Bachelor of Science in Agricultural Engineering

Major Course

Major in Agricultural and Bio-Process Engineering

College

College of Engineering and Agro-Industrial Technology (CEAT)

Adviser/Committee Chair

Yaptenco, Kevin F.

Committee Member

Bato, Pepito M. Nuevo, Perlita A.

Restrictions

Restricted: Not available to the general public and to those bound by the confidentiality agreement. Access is available only after consultation with author/thesis adviser.

Abstract

A greening index on potato tubers was developed based on previous studies. Three different methods (direct color reading, visual evaluation and image analysis) were compared to establish an index in detecting green color. Direct color measurement uses Color reader, measures L*a*b* data from surface through contact. Image analysis,alternatively, utilizes digital camera, for capturing images, Image Acquisition set-up (IAS), for controlled lighting environment, and Image J2X, an open source software for image analysis to extract RGB values. Whereas visual assessment estimates surface color through human perception and approximation. In testing the three methods, simulated retail condition was done to induce greening on potatoes. Using RCBD One-way ANOVA with DMRTat 95% confidence level, it was found out that there isa significant difference among methods and direct color measurement was more sensitive method in detecting green color than the other two methods. Chi-squared test shows that direct shows that direct color reading can be approximated by both image analysis and visual assessment. Moreover, frequency distribution analysis (FDA) concluded that among the three procedures, direct color measurement have the highest precision, and visual assessment have the most varied results .The FDA also suggest that the developed greening index can detect greening on randomly procured samples.

Language

English

Location

UPLB College of Engineering and Agro-Industrial Technology

Call Number

LG 993.5 2013 A2 R67

Document Type

Thesis

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