Factors affecting the caffeine and polyphenol contents of black and green tea infusions.

The effects of product and preparation variables on the in-cup chemical composition of tea extracts is of interest because the appearance and taste characteristics and the possible health effects of a tea liquor arise from the chemical components extracted from the leaf during tea preparation. A comprehensive study was therefore undertaken to determine the contributions of product and preparation variables on the total soluble solids, caffeine, and polyphenol contents of tea extracts. The results of this study show that the variety, growing environment, manufacturing conditions, and grade (particle size) of the tea leaves each influence the tea leaf and final infusion compositions. In addition, the composition of the tea infusion was shown to be influenced by whether the tea was contained in a teabag and, if so, the size and material of construction of the bag. Finally, the preparation method, including the amounts of tea and water used, infusion time, and amount of agitation, was shown to be a major determinant of the component concentrations of tea beverages as consumed. An illustration of the variation introduced by these product and preparation factors is provided by comparing solids, caffeine, and polyphenol contents of green and black tea infusions when commercial products are prepared according to the instructions given on their packaging.     

Application of the Soil and Water Assessment Tool (SWAT) to predict the impact of alternative management practices on water quality and quantity

Alternative land management practices such as conservation or no-tillage, contour farming, terraces, and buffer strips are increasingly used to reduce nonpoint source and water pollution resulting from agricultural activities. Models are useful tools to investigate effects of such management practice alternatives on the watershed level. However, there is a lack of knowledge about the sensitivity of such models to parameters used to represent these conservation practices. Knowledge about the sensitivity to these parameters would help models better simulate the effects of land management. Hence, this paper presents in the first step a sensitivity analysis for conservation management parameters (specifically tillage depth, mechanical soil mixing efficiency, biological soil mixing efficiency, curve number, Manning's roughness coefficient for overland flow, USLE support practice factor, and filter strip width) in the Soil and Water Assessment Tool (SWAT). With this analysis we aimed to improve model parameterisation and calibration efficiency. In contrast to less sensitive parameters such as tillage depth and mixing efficiency we parameterised sensitive parameters such as curve number values in detail.In the second step the analysis consisted of varying management practices (conventional tillage, conservation tillage, and no-tillage) for different crops (spring barley, winter barley, and sugar beet) and varying operation dates. Results showed that the model is very sensitive to applied crop rotations and in some cases even to small variations of management practices. But the different settings do not have the same sensitivity. Duration of vegetation period and soil cover over time was most sensitive followed by soil cover characteristics of applied crops.     

The use of lysimeter data for the test of two soil–water balance models: A case study

Two soil–water balance models were tested by a comparison of simulated with measured daily rates of actual evapotranspiration, soil water storage, groundwater recharge, and capillary rise. These rates were obtained from twelve weighable lysimeters with three different soils and two different lower boundary conditions for the time period from January 1, 1996 to December 31, 1998. In that period, grass vegetation was grown on all lysimeters. These lysimeters are located in Berlin‐Dahlem, Germany. One model calculated the soil water balance using the Richards equation. The other one used a capacitance approach. Both models used the same modified Penman formula for the estimation of potential evapotranspiration and the same simple empirical vegetation model for the calculation of transpiration, interception, and evaporation. The comparisons of simulated with measured model outputs were analyzed using the modeling‐efficiency index IA and the root mean squared error RMSE. At some lysimeters, the uncalibrated application of both models led to an underestimation of cumulative and annual rates of groundwater recharge and capillary rise, despite a good simulation quality in terms of IA and RMSE. A calibration of soil‐hydraulic and vegetation parameters such as maximum rooting depth resulted in a better fit between simulated and observed cumulative and annual rates of groundwater recharge and capillary rise, but in some cases also decreased the simulation quality of both models in terms of IA and RMSE. The results of this calibration indicated that, in addition to a precise determination of the soil water‐retention functions, vegetation parameters such as rooting depth should also be observed. Without such information, the rooting depth is a calibration parameter. However, in some cases, the uncalibrated application of both models also led to an acceptable fit between measured and simulated model outputs.     

Extinction and ecosystem function in the marine benthos

Rapid changes in biodiversity are occurring globally, yet the ecological impacts of diversity loss are poorly understood. Here we use data from marine invertebrate communities to parameterize models that predict how extinctions will affect sediment bioturbation, a process vital to the persistence of aquatic communities. We show that species extinction is generally expected to reduce bioturbation, but the magnitude of reduction depends on how the functional traits of individual species covary with their risk of extinction. As a result, the particular cause of extinction and the order in which species are lost ultimately govern the ecosystem-level consequences of biodiversity loss.     

Forms of memory failure

Memory may fail in a variety of ways. Patients with Korsakoff's syndrome demonstrate global memory deficits similar to those seen in patients with early progressive dementia. Korsakoff's patients, however, may recall rules and principles for organizing information and can gain access to their previously acquired knowledge (semantic memory), whereas recent memory may be grossly impaired. In contrast, dementia patients may have little access to previously acquired knowledge and therefore have great difficulty in organizing and encoding ongoing events. These contrasting forms of memory failure have implications for understanding the structure and mechanisms of memory and learning, particularly the relationship between episodic and semantic memory, as well as the development of therapeutic strategies for cognitive impairments.     

Agronomic traits of soybean cultivars released in different decades after grafting record‐yield cultivar as rootstock

Breeders have seldom considered the selection for root traits during the genetic improvement in soybean. It is hypothesized that grain yield would be increased by the root function improvement, especially for the current cultivars. The objective of this grafting experiment was to determine the effect of record‐yield cultivars L14 or Z35 as rootstocks on agronomic traits of cultivars released in different decades. A total of 11 cultivars, released in different decades, were used to graft onto L14 or Z35 rootstocks. The agronomic traits were measured in the pot‐culture experiments. Grafting cultivars released in different decades onto L14 or Z35 rootstocks resulted in higher yield, 100‐seed mass and apparent harvest index as compared with those of non‐grafted or self‐grafted plants. Grain yield gain of cultivars grafted onto record‐yield cultivar rootstocks was 0.40 g/plant/year from 1966 to 2006, which was larger than that of non‐grafts and self‐grafts (0.27 g/plant/year). The yield of current cultivars should increase more if their root functions were improved.     

Using unsupervised learning techniques to assess interactions among complex traits in soybeans

Soybean yield components and agronomic traits are connected through physiological pathways that impose tradeoffs through genetic and environmental constraints. Our primary aim is to assess the interdependence of soybean traits by using unsupervised machine learning techniques to divide phenotypic associations into environmental and genetic associations. This study was performed on large scale, jointly analyzing 14 quantitative traits in a large multi-parental population designed for genetic studies. We collected phenotypes from 2012 to 2015 from a soybean nested association panel with 40 families of approximately 140 individuals each. Pearson and Spearman correlations measured phenotypic associations. A multivariate mixed linear model provided genotypic and environmental correlations. To evaluate relationships among traits, the study used principal component and undirected graphical models from phenotypic, genotypic, and environmental correlation matrices. Results indicate that high phenotypic correlation occurs when traits display both genetic and environmental correlations. In genetic terms, length of reproductive period, node number, and canopy coverage play important roles in determining yield potential. Optimal grain yield production occurs when the growing environment favors faster canopy closure and extended reproductive length. Environmental associations found among yield components give insight into the nature of yield component compensation. The use of unsupervised learning methods provides a good framework for investigating interactions among various quantitative traits and defining target traits for breeding.     

How climate change might affect tree regeneration following fire at northern latitudes: a review

New Forests - Climate change is projected to increase fire severity and frequency in the boreal forest, but it could also directly affect post-fire recruitment processes by impacting seed...     

Electrokinetic-enhanced remediation of actual arsenic-contaminated soils with approaching cathode and Fe0 permeable reactive barrier

Purpose

The aim of this study was to investigate the remediation efficiency of actual arsenic-contaminated soils by electrokinetic (EK)-enhanced remediation with approaching cathode and Fe⁰ permeable reactive barrier (PRB).

Materials and methods

Experiments were conducted in a lab-made apparatus consisting of the anode reservoir, the soil specimen chamber, and the cathode reservoir.

Results and discussion

In this study, the enhanced combination methods (approaching cathode and Fe⁰-PRB) were assisted for EK remediation of actual arsenic-contaminated soils under a voltage gradient of 1 V/cm and a treatment period of 96 h. Experimental results showed that arsenic accumulated in the anode sections (I, II) of the soil by employing EK alone with an arsenic removal rate of less than 5%. In contrast, EK-enhanced remediation with either approaching cathode (EK/AC) or Fe⁰-PRB (EK/PRB) reduced the arsenic concentrations in both central and anode sections of the soil and afforded the removal rates of 20% in both cases. However, EK-enhanced remediation with the combination of approaching cathode and Fe⁰-PRB (EK/PRB/AC) reached the removal efficiency of 45% without arsenic accumulation in any soil sections. This phenomenon is mainly caused by the approaching cathode that creates an alkaline environment to promote the migration of arsenic, as well as PRB filled with Fe⁰ that achieves the adsorption and immobilization of arsenic.

Conclusions

The highest remediation efficiency was achieved in the EK/PRB/AC test, which was attributed to the fact that the combination of this two methods solved the problem of arsenic accumulation in treated soil and ensured a more thorough arsenic removal. Furthermore, enhanced remediation efficiency does not elevate the costs.