Skip to main content
ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Environmental Microbial & Food Safety Laboratory » Research » Publications at this Location » Publication #286132

Title: Multispectral fluorescence image algorithms for detection of frass on mature tomatoes

item Yang, Chun Chieh
item Kim, Moon
item Millner, Patricia
item Chao, Kuanglin - Kevin Chao
item CHO, BYOUNG-KWAN - Chungnam National University
item Chan, Diane
item MO, CHANG - Rural Development Administration - Korea

Submitted to: Postharvest Biology and Technology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/27/2012
Publication Date: 1/3/2014
Citation: Yang, C., Kim, M.S., Millner, P.D., Chao, K., Cho, B., Chan, D.E., Mo, C. 2014. Multispectral fluorescence image algorithms for detection of frass on mature tomatoes. Postharvest Biology and Technology. 93:1-8.

Interpretive Summary: Frass, the droppings of tomato hornworms and other insects, is one possible vector for the transmission of pathogens such as E. coli and Salmonella to fresh produce. Therefore, rapid detection on postharvest processing lines for frass contamination of fresh produce could help to prevent or minimize the potential safety risks of fresh produce. A simple multispectral fluorescence image processing algorithm was developed for the detection of frass contamination on mature red tomatoes. Contamination spots were applied to the tomatoes using frass dilutions prepared at four different concentrations. The results showed over 99% successful detection of spots created using 0.2 and 0.1 g/ml frass dilutions; spots created using lower concentrations at 0.05 and 0.02 g/ml were more difficult to detect and may require more complex image analysis methods to achieve similar accuracies. The method shows potential use for postharvest screening of fresh tomatoes and could be adapted for screening other agricultural products. The findings will benefit the fresh produce processors, regulators, and scientists with an interest in development of technologies to help reduce food safety risks.

Technical Abstract: A multispectral algorithm derived from hyperspectral line-scan fluorescence imaging under violet LED excitation was developed for the detection of frass contamination on mature tomatoes. The algorithm utilized the fluorescence intensities at five wavebands, 515 nm, 640 nm, 664 nm, 690 nm, and 724 nm, for computation of three ratio functions to detect frass contamination. The contamination spots were created on the tomato surfaces using four low-concentration frass dilutions. The algorithm detected over 99% of the 0.2 g/ml and 0.1 g/ml frass contamination spots and successfully differentiated these spots from tomato skin surfaces, stem scars, and stems. However, differentiation of the spots created from the 0.05 g/ml and 0.02 g/ml frass dilutions was more difficult and the detection of these spots included false-positive detections. This study demonstrates that a simple multispectral fluorescence imaging algorithm based on violet LED excitation could be useful for rapid postharvest detection of frass contamination on tomato processing lines.