• Comparative Assessment of Copper, Iron, and Zinc Contents in Selected Indian (Assam) and South African (Thohoyandou) Tea (Camellia sinensis L.) Samples and Their Infusion: A Quest for Health Risks to Consumer

      Karak, Tanmoy; Paul, Ranjit Kumar; Kutu, Funso Raphael; Mehra, Aradhana; Khare, Puja; Dutta, Amrit Kumar; Bora, Krishnamoni; Boruah, Romesh Kumar; University of Derby (Springer, 2016-06-23)
      Abstract: The current study aims to assess the infusion pattern of three important micronutrients namely copper (Cu), iron (Fe) and zinc (Zn) contents from black tea samples produced in Assam (India) and Thohoyandou (South Africa). Average daily intakes and hazardous quotient were reported for these micronutrients. Total content for Cu, Fe and Zn varied from 2.25 to 48.82 mg kg-1, 14.75 to 148.18 mg kg-1 and 28.48 to 106.68 mg kg-1 respectively. The average contents of each of the three micronutrients were higher in tea leaves samples collected from South Africa than those from India while the contents s in tea infusions in Indian samples were higher than in South African tea samples. Results of this study revealed that the consumption of not more than 600 mL tea infusion produced from 24 g of made tea per day may be beneficial to human in terms of these micronutrients content. Application of nonparametric tests revealed that most of the data sets do not satisfy the normality assumptions. Hence, Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporation the use of both parametric and nonparametric statistical analysis that subsequently revealed significant differences in elemental contents among Indian and South African tea.
    • Detecting macroecological patterns in bacterial communities across independent studies of global soils.

      Ramirez, Kelly S.; Knight, Christopher G.; de Hollander, Mattias; Brearley, Francis Q.; Constantinides, Bede; Cotton, Anne; Creer, Si; Crowther, Thomas W.; Davison, John; Delgado-Baquerizo, Manuel; et al. (Nature, 2017-11-20)
      The emergence of high-throughput DNA sequencing methods provides unprecedented opportunities to further unravel bacterial biodiversity and its worldwide role from human health to ecosystem functioning. However, despite the abundance of sequencing studies, combining data from multiple individual studies to address macroecological questions of bacterial diversity remains methodically challenging and plagued with biases. Here, using a machine-learning approach that accounts for differences among studies and complex interactions among taxa, we merge 30 independent bacterial data sets comprising 1,998 soil samples from 21 countries. Whereas previous meta-analysis efforts have focused on bacterial diversity measures or abundances of major taxa, we show that disparate amplicon sequence data can be combined at the taxonomy-based level to assess bacterial community structure. We find that rarer taxa are more important for structuring soil communities than abundant taxa, and that these rarer taxa are better predictors of community structure than environmental factors, which are often confounded across studies. We conclude that combining data from independent studies can be used to explore bacterial community dynamics, identify potential ‘indicator’ taxa with an important role in structuring communities, and propose hypotheses on the factors that shape bacterial biogeography that have been overlooked in the past.