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plant science Archives - Page 5 of 82 - The Global Plant Council

Image: In this rendition of the macromolecular model of the secondary cell wall in poplar wood, cellulose is shown in white, hemicellulose in green, and lignin in yellow. Credit: Peter Ciesielski, NREL

Researchers Produce First Macromolecular Model of Plant Secondary Cell Wall

By | News, Plant Science

A multidisciplinary approach has enabled researchers to quantitatively define the relative positioning and arrangement of the polymers in Populus wood and to create a computer model that details the findings. The research into solving this macromolecular puzzle may hold the key to efficiently disentangle and deconstruct biomass for conversion to fuels, chemicals, and materials.

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Image: Yew tree with fruits. Paclitaxel and its precursors are produced in the needles and bark of various trees in the Taxus genus. Credit: Alexa / Pixabay

Biosynthesis of paclitaxel unravelled

By | News, Plant Science

Part of modern cancer therapy is the use of chemicals that kill the tumor. Unfortunately, these chemicals are often very complex, difficult to obtain and thus expensive. Researchers have unravelled the biosynthetic pathway of paclitaxel in Yew plants. This discovery might facilitate the production of this very complex molecule which is currently produced with great efforts and high costs.

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Image: Simple road going through a diverse forest. Credit: jusuf111 / Pixabay

New study on the link between biodiversity and climate: How forests smell – a risk for the climate?

By | Climate change, Forestry, News

Plants emit odours for a variety of reasons, such as to communicate with each other, to deter herbivores or to respond to changing environmental conditions. An interdisciplinary team of researchers carried out a study to investigate how biodiversity influences the emission of these substances. For the first time, they were able to show that species-rich forests emit less of these gases into the atmosphere than monocultures.

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Image: Rice field image. Credit: Pixabay

Transforming rice phenotyping: Advanced deep learning models enhance panicle analysis and nitrogen impact studies

By | News, Plant Science

Rice, vital for global food security, faces production challenges during the heading-flowering stage. Traditional phenotyping struggles for large-scale analysis, prompting a shift to advanced computer vision and deep learning. While methods like SIFT and neural networks enhance rice panicle analysis, capturing dynamic growth necessitates merging field cameras with deep learning for precise, real-time monitoring.

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