Cadmium bioconcentration and translocation potential in day-neutral and photoperiod-sensitive hemp grown hydroponically for the medicinal market

Posted on September 26, 2023 By Shawn Douglas Journal articles

In this 2023 article published in the journal Water, Marebesi et al. of the University of Georgia present their findings on phytoremediation of Cadmium (Cd)-contaminated soils using day-neutral and photoperiod-sensitive hemp plants. After a thorough introduction on the topic of using Cannabis plants for phytoremediation (including the flowers), the authors present their materials and methods, focusing on Apricot Auto, Alpha Explorer, Von, and T1 varieties of hemp. They then present the results of their experiments, addressing plant height, biomass yield, Cd concentrations in various plant tissues, nutrient partitioning, and THC/CBD concentrations. They conclude noting that "while Cd concentration was significantly higher in roots, all four varieties were efficient in translocating Cd from roots to shoots." They also conclude that THC/CBD loss is affected by remediation in some cases, as was height and biomass. Finally, they highlight the importance of Cd testing of flowers for medical markets where the plant is used.

NIMS-OS: An automation software to implement a closed loop between artificial intelligence and robotic experiments in materials science

Posted on September 18, 2023 By LabLynx Journal articles

As technological, cultural, and environmental shifts continue to put pressure on the ways academic and private research is conducted, researchers must further strive to get the most out of their work. This holds true across a broad swath of scientific fields, including materials science. Noting the continuing expansion of laboratory automation and software-based tools like artificial intelligence (AI) and machine learning (ML), Tamura et al. emphasize that materials science and novel materials research can benefit greatly from adopting these tools. In this 2023 paper, the authors present their take on this trend, in the form of NIMS-OS, a Python-based system developed to take advantage of completely automated material discovery experiments. After presenting an introduction on the topic, the authors discuss the development philosophy and approach to making NIMS-OS, while also describing use of both the Python command-line tool and the graphical user interface (GUI)-driven version of the software. The authors conclude that their system demonstrates how "various problems for automated materials exploration to be commonly performed," while at the same time being "designed to be easily adaptable to a variety of original robotic systems in materials science."