AIMC Topic: Plant Roots
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Synergistic potential of halophytes and halophilic/halotolerant plant growth-promoting bacteria in saline soil remediation: Adaptive mechanisms, challenges, and sustainable solutions.
Microbiological research
May 22, 2025
Salinity stress poses significant challenges to agriculture, reducing productivity and limiting arable land by causing ionic and osmotic imbalances in plants, disrupting physiological processes, and leading to soil degradation over time. Halophytes a...
Root of Prunus persica (taoshugen) ameliorated renal fibrosis by inhibiting TGF-β signaling via upregulating Pmepa1 in mice with unilateral ureter obstruction.
Journal of ethnopharmacology
Apr 3, 2025
ETHNOPHARMACOLOGICAL RELEVANCE: Various parts of Prunus persica (L.) Batsch (peach) exhibit medicinal properties and are utilized in traditional Chinese medicine (TCM) for therapeutic purposes. Notably, the root of P. persica, referred to as "taoshug...
Machine learning insights for sustainable hydroponic cultivation and growth monitoring of allium cepa using smart hydro kit.
Scientific reports
Mar 24, 2025
This research paper emphasizes the growing importance of Allium Cepa (Onions)-a medicinal plant, as a safe and effective alternative to conventional medicinal therapies for both humans and livestock. The increasing concerns over the high costs and si...
Integrated of Hyperspectral Imaging and Machine Learning Algorithms for Nondestructive Detection of Therapeutic Properties of Plants.
Chemistry & biodiversity
Jan 13, 2025
The approaches used to determine the medicinal properties of the plants are often destructive, labor-intensive, time-consuming, and expensive, making it impossible to analyze their quality analysis online. Performance of hyperspectral imaging (HSI) i...
X-ray irradiation as a potential postharvest treatment for maintaining the quality of lily (Lilium davidii var. unicolor) bulbs and predicting shelf life using an artificial neural network.
Food research international (Ottawa, Ont.)
Dec 31, 2024
This study aimed to investigate the impact of X-ray irradiation pretreatment at varying doses (0.5, 1.0, 1.5, 2.0 kGy) on the preservation quality of lily bulbs and to elucidate its potential regulatory mechanisms. The findings revealed that X-ray ir...
Allelopathic effects of six alfalfa varieties at three stubbles on the germination, seedling and root growth of green foxtail and barnyardgrass.
PloS one
Dec 23, 2024
Alfalfa (Medicago sativa) is known to release allelopathic substances to affect the germination and growth of other plants, which have the potential to be applied in controlling weeds. Green foxtail (Setaria viridis) and barnyardgrass (Echinochloa cr...
Biomimetic Plant-Root-Inspired Robotic Sensor System.
Biosensors
Nov 22, 2024
There are many examples in nature in which the ability to detect is combined with decision-making, such as the basic survival instinct of plants and animals to search for food. We can technically translate this innate function via the use of robotics...
Rapid Raman spectroscopy analysis assisted with machine learning: a case study on Radix Bupleuri.
Journal of the science of food and agriculture
Nov 8, 2024
BACKGROUND: Radix Bupleuri has been widely used for its plentiful pharmacological effects. But it is hard to evaluate their safety and efficacy because the concentrations of components are tightly affected by the surrounding environment. Thus, Radix ...
Carbon dot unravels accumulation of triterpenoid in Evolvulus alsinoides hairy roots culture by stimulating growth, redox reactions and ANN machine learning model prediction of metabolic stress response.
Plant physiology and biochemistry : PPB
Sep 27, 2024
Evolvulus alsinoides, a therapeutically valuable shrub can provide consistent supply of secondary metabolites (SM) with pharmaceutical significance. Nonetheless, because of its short life cycle, fresh plant material for research and medicinal diagnos...
Deep learning models for predicting plant uptake of emerging contaminants by including the role of plant macromolecular compositions.
Journal of hazardous materials
Sep 19, 2024
Deep learning models can predict uptake of emerging contaminants in plants with improved accuracy because they leverage advanced data-driven approaches to capture non-linear relationships that traditional models struggle to address. Traditional model...
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