Submitted to: Journal of Food Engineering
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: August 15, 2011
Publication Date: December 15, 2011
Repository URL:http://handle.nal.usda.gov/10113/54454 Citation: Qin, J., Chao, K., Kim, M.S. 2011. Investigation of Raman chemical imaging for detection of Lycopene changes in tomatoes during postharvest ripening. Journal of Food Engineering. 107(3-4):277-288.
Interpretive Summary: Commercial tomato operations typically harvest mature green tomatoes that are subsequently stored and undergo postharvest ripening prior to sale. Lycopene content is a good maturity indicator as the fruit progresses through the green, breaker, turning, pink, light red, and red stages, but currently is difficult to evaluate without cutting the fruit open. The storage and handling of fruit that is not appropriately sorted by maturity stage can result in food safety and quality problems. For example, postharvest ethylene treatment for ripening of fruits is most efficiently performed for a batch of fruits that all begin at the same stage of ripeness; treating fruits of various ripeness in one batch can cause already ripened fruit to overripen and spoil other fruits, risking loss of an entire batch due to spread of spoilage organisms. In this study, a laboratory-based Raman chemical imaging system was utilized to acquire hyperspectral macro-scale Raman images from cross-sections of tomatoes and from samples of pure lycopene. A spectral information divergence based image classification method was shown to be useful for evaluating lycopene content in the cut tomato samples at different maturity stages, providing maps of the lycopene patterns that develop within the fruit during the postharvest ripening process. This preliminary work with cut tomato samples provides a framework for developing non-destructive Raman methods to evaluate intact tomatoes for lycopene content. Development of a non-destructive method to evaluate lycopene content, and thereby determine fruit maturity, will allow processors to reduce safety and quality problems associated with inaccurate maturity classification of fruits during postharvest procedures, since spoilage and inconsistent ripening within mixed batches can cause safety concerns and increase costs for both processors and consumers.
Lycopene is a major carotenoid in tomatoes and detecting changes in lycopene content can be used to monitor the ripening of tomatoes. Raman chemical imaging is a new technique that shows promise for mapping constituents of interest in complex food matrices. In this study, a benchtop point-scanning Raman chemical imaging system was developed to detect and visualize internal lycopene distribution during postharvest ripening of tomatoes. Tomatoes at different ripeness stages (green, breaker, turning, pink, light red, and red) were cut open for imaging. Hyperspectral Raman images were acquired from fruit cross-sections in the wavenumber range of 200-2500 cm-1 with a spatial resolution of 1 mm. A polynomial curve-fitting method was used to correct for the underlying fluorescence background in the original spectra. A hyperspectral image classification method was developed based on spectral information divergence to identify lycopene in the tomato cross-sections. Raman chemical images were created to visualize the spatial distribution of the lycopene for different ripeness stages. The system was also configured to test the feasibility of utilizing spatially offset Raman spectroscopy technique for subsurface detection of a Teflon slab placed under samples of outer pericarp cut in 5-mm and 10-mm thick slices from green and breaker tomatoes. The results showed that the Raman spectrum of Teflon can be extracted from the measurements of the pericarps placed over the Teflon, demonstrating the potential for future development of a Raman-based nondestructive approach for subsurface detection of lycopene as an indicator of tomato maturity.