Researchers have uncovered the gene LcSVP2 as a key regulator of dormancy in lychee, an evergreen tree. This gene controls when buds rest and also represses flowering. Understanding LcSVP2’s dual role could improve crop management, boosting lychee yields and sustainability in tropical agriculture.
Researchers engineered walnut rootstocks to combat drought. By modifying the JrGA20ox1 gene, they improved drought tolerance in grafted trees. Scions grafted onto gene-suppressed rootstocks retained more chlorophyll and experienced less oxidative stress under drought conditions. This study highlights rootstock modifications as a promising strategy for enhancing crop resilience.
Researchers have uncovered genetic changes behind the timing of plants’ transition from leaf growth to reproduction, akin to “puberty.” This discovery reveals variations in developmental timing even under identical conditions. Understanding these genetic factors could enhance crop uniformity and nutrition, benefiting farmers and consumers alike.
Researchers discovered female-only populations of brown algae, called “Amazons,” that reproduce asexually through parthenogenesis. These algae thrive without males, losing traits like pheromone production and evolving larger gametes. The study offers insights into the genetic and phenotypic changes during the shift from sexual to asexual reproduction.
A new study reveals how different plant species tackle genome doubling, offering insights into cancer. By studying how polyploid plants manage extra DNA, researchers found similarities with polyploid cancers, particularly gliomas. Targeting specific molecules like CENP-E, crucial in both plants and cancers, could inform future cancer therapies.
Researchers have created a deep learning method to analyze social media images taken within protected green spaces to gain insights on human activity distribution as a way to monitor the ecological impacts of these activities.
Environmental biology researchers at the National University of Singapore (NUS) have developed an efficient method for rapidly identifying and classifying human activities within nature reserves at the global level, using social media and deep learning techniques.
Many people visit nature reserves for various reasons, such as hiking to keep fit.
Despite these benefits, it is clear that having too many visitors could lead to overcrowding and negatively impact conservation efforts.
Consequently, to implement more effective land use management strategies for crowd control, governments need to gain insights into how these green spaces are used.
However, as most of these nature reserves cover large land areas, using conventional field surveys to monitor human activities within them can be costly and time-consuming.
The research team, led by Associate Professor L Roman CARRASCO from the Department of Biological Sciences under the NUS Faculty of Science along with his PhD student, Mr Timothy Bing Lun YEE, has developed a technique to process social media images taken within protected areas (PAs) as a proxy for identifying human activities within them.
By parsing these images through a deep learning image tagging model, the human activities depicted within them are automatically detected.
These tagged images are then subsequently grouped into distinct categories of human activities.
They analysed a total of 87,090 photos from 2,813 PAs in 207 countries for this study.
These findings have been published in Scientific Reports.
The researchers made some interesting observations. Most notably, distinct clusters of activity types across PAs aligned closely with expectations.
For instance, there were many photographs of animals and plants in Southeast Asian PAs, while European PAs had numerous photographs of historic castles.
Also, PAs within the same country showed similar activities, even if they had different physical environments.
In explaining the significance of this work, Mr YEE said, “While there have been similar studies, this is possibly the first study that tries to investigate human activities within PAs on a global scale. It demonstrates the utility of social media and deep learning in empowering researchers to investigate pressing environmental issues at a much larger scale.”
Prof CARRASCO added, “The team hopes that this technique can be adopted by nature organisations to monitor land use patterns in nature reserves efficiently and cost-effectively, enabling more targeted conservation efforts to protect ecosystems despite increasing visitor numbers.”
Read the paper: Scientific Reports
Article source: National University of Singapore
Image credit: Researchers from the NUS Department of Biological Sciences extracted images of human activity in protected areas, such as hiking, from Flickr and tagged them to categorise the type of activity in the photo to analyse the global distribution of that activity across different protected areas.
Researchers simulated twilight conditions in a controlled environment to study how Arabidopsis plants respond to varying twilight durations. They found a 30-minute twilight period led to larger plants with more flowers and biomass, compared to shorter or longer durations. This discovery could improve crop yields in agriculture and vertical farming.
By identifying the DNA in spores floating through the air, it’s hoped a new technology can help farmers to tackle crop diseases more effectively while using fewer chemicals.
High in the arid White Mountains of eastern California stand the gnarled, twisted trunks of ancient bristlecone pines. These slow-growing trees quietly weather the ages; at more than 4,000 years old, some are more ancient than the Great Pyramid of Giza.Now, researchers present a novel approach that uses X-ray computed tomography (CT) to capture the wood density of bristlecone tree rings and generate annual resolution reconstructions of ancient temperatures.
The first continent-wide mapping study of plant life across Antarctica reveals growth in previously uncharted areas and is set to inform conservation measures across the region.
