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A Quantitative Analysis of the Proliferation of Microplastics in Williamston’s Waterways

Schafer et al. | Feb 17, 2019

A Quantitative Analysis of the Proliferation of Microplastics in Williamston’s Waterways

Plastic debris can disrupt marine ecosystems, spread contaminants, and take years to naturally degrade. In this study, Wu et al aim to establish an understanding of the scope of Williamston, Michigan’s microplastics problem, as well as to attempt to find the source of these plastics. Initially, the authors hypothesize that the Williamston Wastewater Treatment Plant was the primary contributor to Williamston’s microplastics pollution. Although they find a general trend of increasing concentrations of microplastics from upstream to downstream, they do not pinpoint the source of Williamston’s microplastics pollution in the present research.

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Rhizosphere metagenome analysis and wet-lab approach to derive optimal strategy for lead remediation in situ

Bhat et al. | Jul 18, 2023

Rhizosphere metagenome analysis and wet-lab approach to derive optimal strategy for lead remediation <i>in situ</i>
Image credit: Karolina Grabowska

The Environmental Protection Agency (EPA) reports a significant number of heavy metal-contaminated sites across the United States. To address this public health concern, rhizoremediation using microbes has emerged as a promising solution. Here, a combination of soil microbes were inoculated in the rhizosphere in soil contaminated with 500 parts per million (ppm) of lead. Results showed rhizoremediation is an effective bioremediation strategy and may increase crop productivity by converting nonarable lands into arable lands.

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Performance of Panicum virgatum Cultivars in Competition With Bromus inermis and Differing Amounts of N Fertilizer

Ferris et al. | Mar 04, 2019

Performance of <em>Panicum virgatum</em> Cultivars in Competition With <em>Bromus inermis</em> and Differing Amounts of N Fertilizer

With growing demands for ethanol, many researchers are turning to Panicum virgatum (switchgrass) as a feedstock of cellulosic ethanol. In this study, Ferris and Gillan examine the germination, biomass, nitrogen, survival, and chlorophyll absorbance of two switchgrass cultivars of grown in competition with Bromus inermis (smooth brome) with two varying levels of nitrogen fertilizer. Results presented indicate that during establishment, competition from other species has a greater effect than nitrogen fertilizer.

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Lettuce seed germination in the presence of microplastic contamination

Kochar et al. | Dec 09, 2024

Lettuce seed germination in the presence of microplastic contamination

Microplastic pollution is a pressing environmental issue, particularly in the context of its potential impacts on ecosystems and human health. In this study, we explored the ability of plants, specifically those cultivated for human consumption, to absorb microplastics from their growing medium. We found no evidence of microplastic absorption in both intact and mechanically damaged roots. This outcome suggests that microplastics larger than 10 μm may not be readily absorbed by the root systems of leafy crops such as lettuce (L. sativa).

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A juxtaposition of the effects of natural and chemical fertilizers on Ocimum basilicum

Wilson et al. | Jun 03, 2024

A juxtaposition of the effects of natural and chemical fertilizers on <i>Ocimum basilicum</i>
Image credit: The authors

Agricultural fertilizer application is a key innovation in providing enough food to feed the world. Fertilizers come in various types and farmers must choose which fertilizer is the best for their applications. To learn more about the effectiveness of various fertilizers, Wilson and Rasmus studied the effects of natural and chemical fertilizers on growth of basil plants.

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Enhancing marine debris identification with convolutional neural networks

Wahlig et al. | Apr 03, 2024

Enhancing marine debris identification with convolutional neural networks
Image credit: The authors

Plastic pollution in the ocean is a major global concern. Remotely Operated Vehicles (ROVs) have promise for removing debris from the ocean, but more research is needed to achieve full effectiveness of the ROV technology. Wahlig and Gonzales tackle this issue by developing a deep learning model to distinguish trash from the environment in ROV images.

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