This article explores the largely unstudied impact of noise pollution on plant life. By exposing Arabidopsis thaliana seedlings to urban traffic noise, the study found a significant increase in seedling growth, alongside substantial changes in gene expression. This research reveals critical insights into how noise pollution affects plant physiology and contributes to a broader understanding of its ecological impacts, helping to guide future efforts in ecosystem conservation.
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Groundwater prediction using artificial intelligence: Case study for Texas aquifers
Here, in an effort to develop a model to predict future groundwater levels, the authors tested a tree-based automated artificial intelligence (AI) model against other methods. Through their analysis they found that groundwater levels in Texas aquifers are down significantly, and found that tree-based AI models most accurately predicted future levels.
Read More...Investigating the Role of Biotic Factors in Host Responses to Rhizobia in the System Medicago truncatula
Nitrogen-fixing bacteria, such as the legume mutualist rhizobia, convert atmospheric nitrogen into a form that is usable by living organisms. Leguminous plants, like the model species Medicago truncatula, directly benefit from this process by forming a symbiotic relationship with rhizobia. Here, Rathod and Rowe investigate how M. truncatula responds to non-rhizobial bacterial partners.
Read More...Milkweed sustainability in the Sonoran Desert: A. erosa is more water-efficient compared to two other species
This study assesses the capacity for milkweed species, an important host plant for Monarch butterflies, to grow in desert environments with different water levels.
Read More...Assessing grass water use efficiency through smartphone imaging and ImageJ analysis
Overwatering and underwatering grass are widespread issues with environmental and financial consequences. This study developed an accessible method to assess grass water use efficiency (WUE) combining smartphone imaging with open access color unmixing analysis. The method can be applied in automated irrigation systems or apps, providing grass WUE assessment for regular consumer use.
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