Über den Vitamingehalt einiger griechischer Früchte

European Food Research and Technology - Griechische Calmata-Kranzfeigen wurden auf ihren Vitamingehalt geprüft. Sie enthielten in 1 g 2,4 internationale Einheiten Vitamin A, etwa 0,48...     

The effect of postharvest ripening on strawberry bioactive composition and antioxidant potential

BACKGROUND: The aim of the present work was to evaluate the phytochemical profile and the antioxidant activity of strawberry fruit (cv. Camarosa) upon postharvest ripening at room temperature (20 °C) and to correlate them with qualitative attributes. RESULTS: ‘Camarosa’ fruit retained an appreciable postharvest performance for up to 1 day shelf life; thereafter substantial quality deterioration was observed. An increased phenolic content, mainly attributed to hydroxycinnamic acids, flavonols and anthocyanins, was monitored after 3 days maintenance at 20 °C. The chromatographic fingerprint of athocyanins showed that pelargonidin‐3‐glucoside was the major anthocyanin, which increased with the increase of shelf life period, while cyanidin‐3‐glucoside and pelargonidin‐3‐rutinoside were found at lower concentrations. The potent radical scavenging activity, evaluated with four in vitro assays, showed a higher antioxidant capacity after 3 and 1 days of shelf life. In addition, the antioxidant effect of strawberry fruit extracts on lipid substrates and on an emulsion system showed a significant inhibition in the formation of conjugated diene hyperoxides. Interestingly, no direct correlation between the phytochemical profile and the quality attributes exist. CONCLUSION: ‘Camarosa’ fruit had acceptable quality attributes for fresh consumption and at the same time a high phytochemical content up to 1 day shelf life. The over‐ripe fruit continued to be an excellent reservoir of natural antioxidants, pointing to its potential use as food antioxidant and nutritional supplement. Copyright © 2011 Society of Chemical Industry     

Machine Learning Utilization for Bed Load Transport in Gravel-Bed Rivers

Three data-driven techniques, namely artificial neural networks, adaptive-network-based fuzzy inference system, and symbolic regression based on genetic programming, are employed for the prediction of bed load transport rates in gravel-bed steep mountainous streams and rivers in Idaho (U.S.A.), and the potential of several input variables is investigated. The input combinations that were tested are based, mainly, on unit stream power, stream power, and shear stress, and exhibited similarly good performance, with respect to the machine learning technique used, accentuating the importance of the regression model. The derived models are robust, generalize very well in unseen data, and generated results superior to those of some of the widely used bed load formulae, without the need to set a threshold for the initiation of motion, and consequently avoid predicting erroneous zero transport rates.     

A Machine Learning Approach for the Mean Flow Velocity Prediction in Alluvial Channels

Water Resources Management - In natural alluvial channels, the determination of the flow resistance constitutes a problem with additional complexity compared to rigid bed channels, due to the bed...     

Exploring the antioxidant potential of Teucrium polium extracts by HPLC–SPE–NMR and on-line radical-scavenging activity detection

Teucrium polium is a popular medicinal plant that is used in the daily diet and the in vitro and in vivo antioxidant potency of its extracts has been widely investigated. In the present work, polar extracts from T. polium were analyzed in terms of its composition and radical-scavenging activity with the employment of the state-of-the-art HPLC-SPE-NMR and HPLC-DPPH techniques in the search of new antioxidant agents for food industry. NMR and MS data revealed the presence of phenylpropanoid glycosides verbascoside and poliumoside, the flavones apigenin and its derivatives and two methoxyflavones. The on-line DPPH experiments showed that poliumoside is the most active component of the extracts and the antioxidant potential of T. polium polar extracts is mainly attributed to phenylpropanoid glycosides (66–80%). Our results suggested that T. polium extracts could be a promising source of natural antioxidants. This holistic approach also revealed that poliumoside or polar extracts of T. polium can be used in food industry as antioxidant agents with natural origin. The HPLC-SPE-NMR and HPLC-DPPH analysis of the extracts was performed for first time in the same device without any modification of the instrumentation, avoiding the need for isolation of the individual components.     

Computation of Drought Index SPI with Alternative Distribution Functions

The Standardized Precipitation Index (SPI) is widely used as drought meteorological index, to identify the duration and/or severity of a drought. The SPI is usually computed by fitting the gamma probability distribution to the observed precipitation data. In this work, the possibility to calculate SPI by fitting to the precipitation data the normal and the log-normal probability distributions was studied. For this purpose, 19 time series of monthly precipitation of 76?years were used, and the assumption that the gamma probability distribution would provide better representation of the precipitation data than log-normal and normal distributions, at various time scales (1, 3, 6, 12 and 24?months) was tested. It is concluded that for SPI of 12 or 24?months, the log-normal or the normal probability distribution can be used for simplicity, instead of gamma, producing almost the same results.