Browse Articles

In this study, the authors test the longevity of a anti-mite compound, amitraz, in commercially-sold strips and the age-dependent efficacy of these strips in preventing honey bee colony collapse by ectoparasitic mite Varroa destructor.

Scientist are investigating the use of methane-consuming bacteria to aid the growing problem of rising greenhouse gas emissions. While previous studies claim that low-frequency electromagnetic fields can accelerate the growth rate of these bacteria, Chu et al. demonstrate that this fundamental ideology is not on the same wavelength with their data.

Plant pathogens can cause significant crop loss each year, but controlling them with bactericides or antibiotics can be costly and may be harmful to the environment. Green tea naturally contains polyphenols, which have been shown to have some antimicrobial properties. In this study, the authors show that green tea extract can inhibit growth of the plant pathogen Pseudomonas syringae pv. tomato and may be useful as an alternative bactericide for crops.

Here, the authors sought to investigate the effects of water current on the growth of colonies of duckweed, a floating plant that forms colonies in silent ponds, marshes, lakes , and streams in North America. They found that current flow mediates the formation of colonies, disrupting and recreating the colonies which provides the opportunity for reorganizations that were identified as beneficial.

In this study, the authors investigate the combinatorial effects of CO₂ plus other environmental factors including salinity, temperature, acidity, and drought on how effectively plants can transport water and carbon through their stomata.

Here, seeking to identify an optimal method to classify tree species through remote sensing, the authors used a few machine learning algorithms to classify forest tree species through multispectral satellite imagery. They found the Random Forest algorithm to most accurately classify tree species, with the potential to improve model training and inference based on the inclusion of other tree properties.

In this article, the authors compare different resource-efficient farming methods for the vegetable Lactuca sativa. They compared hydroponics (solid growth medium with added nutrients) to aquaponics (water with fish waste to provide nutrients) and determined efficacy by measuring plant height over time. While both systems supported plant growth, the authors concluded that aquaponics was the superior method for supporting Lactuca sativa growth. These findings are of great relevance as we continue to find the most sustainable and efficient means for farming.

The authors test whether basil can grow in a simulated Martian soil improved with a waste-based fertilizer called Milorganite.

Chemical preservatives are often used to reduce grain spoilage due to mold, but can have harmful heath and environmental effects. In this study, the authors tested three low toxic compounds for their effects on mold growth on corn kernels and found that all three were successful at slowing growth.

This study hypothesized that a machine learning model could accurately predict the severity of California wildfires and determine the most influential meteorological factors. It utilized a custom dataset with information from the World Weather Online API and a Kaggle dataset of wildfires in California from 2013-2020. The developed algorithms classified fires into seven categories with promising accuracy (around 55 percent). They found that higher temperatures, lower humidity, lower dew point, higher wind gusts, and higher wind speeds are the most significant contributors to the spread of a wildfire. This tool could vastly improve the efficiency and preparedness of firefighters as they deal with wildfires.