Phenolic profile of different red and yellow raspberry varieties during ripening

Rubus species, including raspberries, have been used since ancient times for the treatment of wounds, diarrhea, colic pain, diabetes, etc.[1]. Being among the fruits with higher antioxidant contents, raspberries are receiving increasing attention as a source of potentially healthy compounds that can help prevent cardiovascular disease and diabetes mellitus [2]. A large part of the health effects attributed to berries is supposed to be due to polyphenolic compounds. The majority of raspberries polyphenols are ellagitannins, but they also contain large amounts of anthocyanins (in red raspberries) and smaller amounts of hydroxycinnamic acids, flavonols, flavan-3-ols and proanthocyanidins [3]. Yellow raspberries, which lack anthocyanins at all, seem to be as effective or even more effective than their red counterparts at inhibiting enzymes with potential impact on chronic diabetes or hypertension [4, 5]. From the biosynthetic point of view there is as yet no information on where the block of the anthocyanin pathway in yellow raspberries could be. In this study a targeted UPLC-MS/MS method recently developed by our lab was used to screen 140 phenolic compounds including benzoates, phenylpropanoids, coumarins, stilbenes, dihydrochalcones and flavonoids, using MRM transitions for accurate quantification. The fruits of different plants of 4 red and 6 yellow raspberry varieties, at different ripening stages (green, turning and ripe) where analyzed. Around 34 phenolic compounds where detected above the quantification limit at the different ripening stages. This allowed to obtain not only a profile of the phenolic composition of the different raspberry varieties, at different stages, but also to highlight the different tendencies in the variation of concentration of each of the different compounds during ripening. Furthermore, a general biosynthetic scheme and a prediction of the mechanism underlaying the loss of anthocyanisn in yellow raspberries can be predicted [1] G. Rocabado, L. Bedoya, M. Abad, P. Bermejo, Natural Product Communications, 3 (2008) 423-436. [2] J. Beekwilder, R.D. Hall, C.H.R. de Vos, Biofactors, 23 (2005) 197-205. [3] A.V. Rao, D.M. Snyder, Journal of Agricultural and Food Chemistry, 58 (2010) 3871-3883. [4] S. Cheplick, Y.-I. Kwon, P. Bhowmik, K. Shetty, J Food Biochemistry, 31 (2007) 656-679. [5] L. Zhang, J. Li, S. Hogan, H. Chung, G.E. Welbaum, K. Zhou, Food Chemistry, 119 (2010) 592-599.