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Measurements of lycopene contents in fruit: A review of recent developments in conventional and novel techniques

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Abstract

Lycopene is a biologically active phytochemical reported in fruit. Conventional techniques such as high performance liquid chromatography (HPLC) and thin layer chromatography (TLC) have been in existence for measuring lycopene in fruit, but these methods are destructive with relative accuracy and speed. Other novel spectroscopic and imaging approaches, which are more reliable and fast, have recently been developed to investigate complex components such as lycopene, total soluble solids, etc. in fruit. The current review attempts to highlight the potential of both conventional and novel techniques in evaluating lycopene contents of fruit. The novel techniques include both spectroscopic methods such as near infrared spectroscopy and Raman spectroscopy and spectral imaging approaches such as multispectral imaging, hyperspectral imaging and Raman imaging. The principles of these techniques are summarized, their detailed applications are discussed, and future trends are also presented. Both traditional and novel techniques highlighted in the current review can be used for assessing the distribution and concentration of lycopene in various fruit. Although novel spectroscopic and spectral imaging approaches may in the near future replace conventional methods, because conventional methods are typically often offline, destructive and time-consuming, which also require the use of chemicals.

Acknowledgments

The authors are grateful to the National Key R&D Program of China (2017YFD0400404) for its support. This research was also supported by the Collaborative Innovation Major Special Projects of Guangzhou City (201604020007), the Guangdong Provincial Science and Technology Plan Projects (2015A020209016, 2016A040403040), the Fundamental Research Funds for the Central Universities (2017MS067, 2017MS075), the International and Hong Kong – Macau – Taiwan Collaborative Innovation Platform of Guangdong Province on Intelligent Food Quality Control and Process Technology & Equipment (2015KGJHZ001), the Guangdong Provincial R & D Centre for the Modern Agricultural Industry on Non-destructive Detection and Intensive Processing of Agricultural Products, the Common Technical Innovation Team of Guangdong Province on Preservation and Logistics of Agricultural Products (2016LM2154) and the Innovation Centre of Guangdong Province for Modern Agricultural Science and Technology on Intelligent Sensing and Precision Control of Agricultural Product Qualities. In addition, Abid Hussain is in receipt of a PhD scholarship from the China Scholarship Council.

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