Related Experiment Video
Updated: Sep 20, 2025

Profiling Volatile Compounds in Blackcurrant Fruit using Headspace Solid-Phase Microextraction Coupled to Gas Chromatography-Mass Spectrometry
Published on: June 9, 2021
Screening of Naturally Grown European Cranberrybush (Viburnum opulus L.) Genotypes Based on Physico-Chemical
Ayşen Melda Çolak1, Kerem Mertoğlu2,3, Fatma Alan4
1Department of Horticulture, Faculty of Agriculture, Usak University, 64000 Usak, Turkey.
Abstract:
It has become very important to offer species with high nutritional value as fresh or processed products for human consumption in their daily diet for balanced nutrition. In the scope of this study, 15 naturally grown European Cranberry bush (ECB) genotypes that naturally grown were characterized in terms of horticultural characteristics. Fruit length, fruit width, fruit weight, the number of fruits per each cluster and cluster weight were determined within the ranges of 8.78−10.96 mm, 7.93−10.84 mm, 0.21−0.70 g, 31−121, and 7.70−66.67 g, respectively. Ranking of the average values of examined organic acids obtained from all genotypes found as; malic acid (11,419 mg L−1) > citric acid (1926 mg L−1) > ascorbic acid (581 mg L−1) > oxalic acid (561 mg L−1). Total phenolic content (TPC) and total flavonoid content (TFC) were found at high levels in ECB with 2922−3475 mg gallic acid equivalent (GAE) L−1 and 1463−3163 mg quercetin equivalents (QE) L−1, respectively. While pomological characteristics were found to be highly positive correlated with each other, they were negatively correlated with chemical properties. Low pH was found to be an important parameter to obtain higher amounts of phytochemicals such as TPC, TFC, organic and phenolic acids correlated with strong antioxidant effects. The obtained results will be useful for both germplasm enrichment and cultivation.
More Related Videos
12:32Colletotrichum fioriniae Development in Water and Chloroform-based Blueberry and Cranberry Floral Extracts
Published on: April 12, 2019
10:25Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements
Published on: June 28, 2016