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Here the authors investigated the use of an affordable gas sensor to detect volatile organic compound (VOC) emissions as an early indicator of tree disease, finding statistically significant differences in VOCs between diseased and non-diseased ash, beech, and maple trees. They suggest this sensor has potential for widespread early disease detection, but call for further research with larger sample sizes and diverse locations.

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.

The authors propose a method to recycle Christmas tree needles into a non-toxic reducing agent for synthesizing copper nanoparticles.

Each year, invasive tree roots cause large amounts of damage to underground pipes. While this is usually due to leaks and cracks, tree roots can also invade pipes that are structurally sound. We are interested in investigating whether plant roots have an affinity towards flowing water, measured through mass, even when the running water is not in direct contact with soil. We tested this by creating a choice chamber with water running under one end and no stimulus on the other end. Overall, the masses of the roots growing towards flowing water were greater than the masses of the roots growing towards the end with no stimulus, showing that plant roots did have an affinity towards flowing water.

In this study, the authors investigated the antimicrobial properties of the tree species, Populus balsamifera. It was observed that the extract of the buds of P. balsamifera was highly effective against gram-positive bacteria. This helps to indicate the potential use of P. balsamifera in the medical field to eliminate gram-positive bacteria.

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.

Medicinal plants could be a good source of medication to combat antibiotic resistance. Dombeya wallichii, which is commonly called Pink Ball Tree in the family Sterculiaceae, has been documented to have medicinal potential. We observed the highest antibacterial activity in the stem extracts, followed by leaf and bark extracts. The extracts were more effective against tested Gram-positive bacteria when compared with Gram-negative strains.

Over the last few decades, childhood stunting has persisted as a major global challenge. This study hypothesized that TPTO (Tree-based Pipeline Optimization Tool), an AutoML (automated machine learning) tool, would outperform all pre-existing machine learning models and reveal the positive impact of economic prosperity, strong familial traits, and resource attainability on reducing stunting risk. Feature correlation plots revealed that maternal height, wealth indicators, and parental education were universally important features for determining stunting outcomes approximately two years after birth. These results help inform future research by highlighting how demographic, familial, and socio-economic conditions influence stunting and providing medical professionals with a deployable risk assessment tool for predicting childhood stunting.

Many species of trees are distributed widely around the world, though not always in a way that makes immediate sense. The authors here use genetic information to help explain the geographic distribution of various conifer species throughout the world.

The authors develop and test a machine learning algorithm for predicting diabetes diagnoses.